Model-Based Reconstruction of the Grounding System Surface Potential Distribution by Means of Monte Carlo Markov Chain Simulation

Abstract

Accurate reconstruction of the earth surface potential distribution functional shape from a discrete set of measuring points is important in the grounding system safety assessment process. Commonly used scattered data interpolation techniques may produce unreliable results under unfavorable sampling conditions. A novel model-based mathematical approach to the surface potential distribution reconstruction is proposed, which is based on the stochastic approach to the inverse problem solution, implemented by means of the Monte Carlo Markov chain simulation. The reconstruction quality of the potential distribution is improved considerably by incorporating the physical model of the grounding grid behavior into the interpolation algorithm, particularly for sparse and irregular noisy sampling sets.

Keywords:

• Monte Carlo Markov chains
• Metropolis-Hastings algorithm
• inverse problems
• data fitting
• grounding systems